The Role of Large Language Models in Transforming Emergency Medicine: Scoping Review

• Published in: JMIR medical informatics Vol. 12; p. e53787
• Main Authors: Preiksaitis, Carl, Ashenburg, Nicholas, Bunney, Gabrielle, Chu, Andrew, Kabeer, Rana, Riley, Fran, Ribeira, Ryan, Rose, Christian
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 10.05.2024
• Subjects: Artificial intelligence; Clinical decision making; Emergency medical care; Emergency preparedness; Large language models; education; medical education; United States; emergency medicine; Med-PaLM; medical training; GPT; Preferred Reporting Items for Systematic Reviews and Meta-Analyses; decision support; LLM; ethics; large language model; Bard; artificial intelligence; generative pretrained transformer; NLP; ChatGPT; China; BERT; physician; communication; US; scoping review; Bidirectional Encoder Representations from Transformers; natural language processing; AI; PRISMA; health literacy; clinical decision support; Pathways Language Model; workflow efficiency; emergency care; risk; AI literacy
• ISSN: 2291-9694; 2291-9694
• DOI: 10.2196/53787

Artificial intelligence (AI), more specifically large language models (LLMs), holds significant potential in revolutionizing emergency care delivery by optimizing clinical workflows and enhancing the quality of decision-making. Although enthusiasm for integrating LLMs into emergency medicine (EM) is...